Au Canada, les taux d’incidence du cancer et de mortalité attribuable au cancer diffèrent-ils selon l’origine ethnique?
Bibliographic record
Abstract
Il a été démontré que les taux d'incidence du cancer varient selon l'origine ethnique. À l'échelle internationale, on constate une prise de conscience grandissante des inégalités interethniques en matière de santé, et un intérêt accru à en rendre compte. Cette étude vise à évaluer les taux d'incidence et de mortalité du cancer selon l'origine ethnique au Canada. Pour ce faire, elle s'appuie sur les données couplées de la Cohorte santé et environnement du recensement canadien de 2006, du Registre canadien du cancer et de la Base canadienne de données de l'état civil - Décès, pour déterminer les cas de cancer et la mortalité de 2006 à 2016. L'origine ethnique a été classée selon les groupes suivants : origines non autochtones nord-américaines, origines européennes, origines des Caraïbes, origines de l'Amérique latine centrale et du Sud, origines africaines, origines asiatiques de l'Est, origines sud-asiatiques, origines de l'Asie centrale occidentale et du Moyen-Orient."
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".